AceGPT 7B Chat — Hardware Requirements & GPU Compatibility
Chat
456 downloads
13 likesSpecifications
- Publisher
- FreedomIntelligence
- Parameters
- 7B
- Architecture
- LlamaForCausalLM
- Context Length
- 2,048 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2024-03-04
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does AceGPT 7B Chat Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| FP16 | 16.00 | 15.4 GB | — | 14.00 GB | Full half-precision — baseline for inference |
Which GPUs Can Run AceGPT 7B Chat?
FP16 · 15.4 GBAceGPT 7B Chat (FP16) requires 15.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 20+ GB is recommended. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run AceGPT 7B Chat?
FP16 · 15.4 GB27 devices with unified memory can run AceGPT 7B Chat, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does AceGPT 7B Chat need?
AceGPT 7B Chat requires 15.4 GB of VRAM at FP16.
VRAM = Weights + KV Cache + Overhead
Weights = 7B × 16 bits ÷ 8 = 14 GB
KV Cache + Overhead ≈ 1.4 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
FP1615.4 GB- Can I run AceGPT 7B Chat on a Mac?
AceGPT 7B Chat requires at least 15.4 GB at FP16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run AceGPT 7B Chat locally?
Yes — AceGPT 7B Chat can run locally on consumer hardware. At FP16 quantization it needs 15.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is AceGPT 7B Chat?
At FP16, AceGPT 7B Chat can reach ~190 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~43 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 15.4 × 0.55 = ~190 tok/s
Estimated speed at FP16 (15.4 GB)
AMD Instinct MI300X~190 tok/sNVIDIA GeForce RTX 4090~43 tok/sNVIDIA H100 SXM~142 tok/sAMD Instinct MI250X~117 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of AceGPT 7B Chat?
At FP16, the download is about 14.00 GB.
- Which GPUs can run AceGPT 7B Chat?
17 consumer GPUs can run AceGPT 7B Chat at FP16 (15.4 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 5 GPUs have plenty of headroom for comfortable inference.
- Which devices can run AceGPT 7B Chat?
27 devices with unified memory can run AceGPT 7B Chat at FP16 (15.4 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.